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ATR Volatility giua64ATR Volatility giua64 – Smart Signal + VIX Filter 📘 Script Explanation (in English) Title: ATR Volatility giua64 – Smart Signal + VIX Filter This script analyzes market volatility using the Average True Range (ATR) and compares it to its moving average to determine whether volatility is HIGH, MEDIUM, or LOW. It includes: ✅ Custom or preset configurations for different asset classes (Forex, Indices, Gold, etc.). ✅ An optional external volatility index input (like the VIX) to refine directional bias. ✅ A directional signal (LONG, SHORT, FLAT) based on ATR strength, direction, and external volatility conditions. ✅ A clean visual table showing key values such as ATR, ATR average, ATR %, VIX level, current range, extended range, and final signal. This tool is ideal for traders looking to: Monitor the intensity of price movements Filter trading strategies based on volatility conditions Identify momentum acceleration or exhaustion ⚙️ Settings Guide Here’s a breakdown of the user inputs: 🔹 ATR Settings Setting Description ATR Length Number of periods for ATR calculation (default: 14) ATR Smoothing Type of moving average used (RMA, SMA, EMA, WMA) ATR Average Length Period for the ATR moving average baseline 🔹 Asset Class Preset Choose between: Manual – Define your own point multiplier and thresholds Forex (Pips) – Auto-set for FX markets (high precision) Indices (0.1 Points) – For index instruments like DAX or S&P Gold (USD) – Preset suitable for XAU/USD If Manual is selected, configure: Setting Description Points Multiplier Multiplies raw price ranges into useful units (e.g., 10 for Gold) Low Volatility Threshold Threshold to define "LOW" volatility High Volatility Threshold Threshold to define "HIGH" volatility 🔹 Extended Range and VIX Setting Description Timeframe for Extended High/Low Used to compare larger price ranges (e.g., Daily or Weekly) External Volatility Index (VIX) Symbol for a volatility index like "VIX" or "EUVI" Low VIX Threshold Below this level, VIX is considered "low" (default: 20) High VIX Threshold Above this level, VIX is considered "high" (default: 30) 🔹 Table Display Setting Description Table Position Where the visual table appears on the chart (e.g., bottom_center, top_left) Show ATR Line on Chart Whether to display the ATR line directly on the chart ✅ Signal Logic Summary The script determines the final signal based on: ATR being above or below its average ATR rising or falling ATR percentage being significant (>2%) VIX being high or low Conditions Signal ATR rising + high volatility + low VIX LONG ATR falling + high volatility + high VIX SHORT ATR flat or low volatility or low %ATR FLAT
Pine Script®指標
由giua64提供
Candlestick High/Low Labels📌 Indicator Name: Candlestick High/Low Labels 🧠 Author: Precious Life Dynamics (@Precious_Life) 📋 Description: The Candlestick High/Low Labels indicator highlights recent price extremes by placing labels above highs and below lows of previous candles. Additionally, it displays a live OHLCV dashboard in the bottom-right corner, offering a quick overview of recent market data. This tool is especially useful for: Identifying support/resistance levels Tracking candle behavior Visualizing volume trends in context ⚙️ How It Works: 🔸 High/Low Labels: Each of the most recent candles (based on Candle Lookback) is annotated as follows: 🔹 Red label above each candle’s high 🔹 Green label below each candle’s low 🔹 Price values are rounded (no decimals) 🔹 Labels are dynamically updated; old ones are removed 🔹 Label visibility can be toggled via the Show Labels input 🔸 OHLCV Dashboard: A real-time data table appears in the bottom-right corner of the chart. It displays the last N candles (based on Dashboard Lookback) with the following fields: 🔹 Candle Number (1 = most recent) 🔹 Open, High, Low, Close 🔹 Volume 🔹 Values are rounded for readability 🔹 White background with black text ensures high visual clarity 🔧 Customizable Inputs: ✅ Candle Lookback → Number of candles to label (default: 10) ✅ Show Labels → Toggle High/Low label display on/off ✅ Dashboard Lookback → Number of candles shown in the OHLCV table (default: 10) 🎯 Use Cases: 🔹 Identify recent price extremes and reaction zones 🔹 Spot dynamic support and resistance levels 🔹 Observe how candles behave at swing highs/lows 🔹 Monitor volume activity in relation to price 🔹 Use as a clean visual tool for scalping and intraday trading 📝 Notes: 🔹 This indicator is purely visual – it does not generate trade signals 🔹 Best suited for traders who value clear, real-time price structure feedback
Pine Script®指標
由Precious_Life提供
Breakout BTC 5min 📈 BTC Breakout Strategy – 5-Minute Chart This strategy captures breakout opportunities on BTC using a 5-minute timeframe. A trade is triggered only when all of the following conditions are met: ✅ Breakout above/below the recent 20-bar high/low ✅ Trend confirmation with EMA 20 > EMA 50 for longs, EMA 20 < EMA 50 for shorts ✅ Momentum confirmation using RSI (> 60 for longs, < 40 for shorts) ✅ High volume: current volume > 1.5× its 20-period moving average ⏰ Active only between 9:00 and 18:00 UTC 🔁 Trailing stop (0.4%) automatically manages exits Trade signals are visually marked on the chart with labeled arrows.
Pine Script®策略
由Boubizee提供
Statistical Reliability Index (SRI)Statistical Reliability Index (SRI) The Statistical Reliability Index (SRI) is a professional financial analysis tool designed to assess the statistical stability and reliability of market conditions. It combines advanced statistical methods to gauge whether current market trends are statistically consistent or prone to erratic behavior. This allows traders to make more informed decisions when navigating trending and choppy markets. Key Concepts: 1. Extrapolation of Cumulative Distribution Functions (CDF) What is CDF? A Cumulative Distribution Function (CDF) is a statistical tool that models the probability of a random variable falling below a certain value. How it’s used in SRI: The SRI utilizes the 95th percentile CDF of recent returns to estimate the likelihood of extreme price movements. This helps identify when a market is experiencing statistically significant changes, crucial for forecasting potential breakouts or breakdowns. Weight in SRI: The weight of the CDF extrapolation can be adjusted to emphasize its impact on the overall reliability index, allowing customization based on the trader's preference for tail risk analysis. 2. Bias Factor (BF) What is the Bias Factor? The Bias Factor measures the ratio of the current market price to the expected mean price calculated over a defined period. It represents the deviation from the typical price level. How it’s used in SRI: A higher bias factor indicates that the current price significantly deviates from the historical average, suggesting a potential mean reversion or trend exhaustion. Weight in SRI: Adjusting the Bias Factor weight lets users control how much this deviation influences the SRI, balancing between momentum trading and mean reversion strategies. 3. Coefficient of Variation (CV) What is CV? The Coefficient of Variation (CV) is a statistical measure that expresses the ratio of the standard deviation to the mean. It indicates the relative variability of asset returns, helping gauge the risk-to-return consistency. How it’s used in SRI: A lower CV indicates more stable and predictable price behavior, while a higher CV signals increased volatility. The SRI incorporates the inverse of the normalized CV to reflect price stability positively. Weight in SRI: By adjusting the CV weight, users can prioritize consistent price movements over erratic volatility, aligning the indicator with risk tolerance and strategy preferences. Interpreting the SRI: 1. SRI Plot: The SRI plot dynamically changes color to reflect market conditions: Aqua Line: Indicates uptrend stability, signaling statistically consistent upward movements. Fuchsia Line: Indicates downtrend stability, where statistically reliable downward movements are present. The overlay background shifts between colors: Aqua Background: Signifies statistical stability, where trends are historically consistent. Fuchsia Background: Indicates statistical instability, often associated with trend uncertainty. Yellow Background: Marks choppy periods, where statistical data suggests that market conditions are not conducive to reliable trading. 2. SRI Volatility Plot: Displays the volatility of the SRI itself to detect when the indicator is stable or unstable: Blue Area Fill: Signifies that the SRI is stable, indicating trending conditions. Yellow Area Fill: Represents choppy or unstable SRI movements, suggesting sideways or unreliable market conditions. A Chop Threshold Line (dotted yellow) highlights the maximum acceptable SRI volatility before the market is considered too unpredictable. 3. Stability Assessment: Stable Trend (No Chop): The SRI is smooth and consistent, often accompanied by aqua or fuchsia lines. Volatility remains below the chop threshold, indicating a low-risk, trend-following environment. Chop Mode: The SRI becomes erratic, and the volatility plot spikes above the threshold. Marked by a yellow shaded background, indicating uncertain and non-trending conditions. [Trend Identification: Use the color-coded SRI line and background to determine uptrend or downtrend reliability. Be cautious when the SRI volatility plot shows yellow, as this signals trading conditions may not be reliable. Practical Use Cases: Trend Confirmation: Utilize the SRI plot color and background to confirm whether a detected trend is statistically reliable. Chop Mode Filtering: During yellow chop periods, it is advisable to reduce trading activity or adopt range-bound strategies. Strategy Filter: Combine the SRI with trend-following indicators (like moving averages) to enhance entry and exit accuracy. Volatility Monitoring: Pay attention to the SRI volatility plot, as spikes often precede erratic price movements or trend reversals. Disclaimer: The Statistical Reliability Index (SRI) is a technical analysis tool designed to aid in market stability assessment and trend validation. It is not intended as a standalone trading signal generator. While the SRI can help identify statistically reliable trends, it is essential to incorporate additional technical and fundamental analysis to make well-informed trading decisions. Trading and investing involve substantial risk, and past performance does not guarantee future results. Always use risk management practices and consult with a financial advisor to tailor strategies to your individual risk profile and objectives.
Pine Script®指標
由RWCS_LTD提供
Granger Causality Flow IndicatorGranger Causality Flow Indicator (GC Flow) █ OVERVIEW The Granger Causality Flow Indicator (GC Flow) attempts to quantify the potential predictive relationship between two user-selected financial instruments (Symbol X and Symbol Y). In essence, it explores whether the past values of one series (e.g., Symbol X) can help explain the current value of another series (e.g., Symbol Y) better than Y's own past values alone. This indicator provides a "Granger Causality Score" (GC Score) for both directions (X → Y and Y → X). A higher score suggests a stronger statistical linkage where one series may lead or influence the other. The indicator visualizes this "flow" of potential influence through background colors and on-chart text. Important Note: "Granger Causality" does not imply true economic or fundamental causation. It is a statistical concept indicating predictive power or information flow. This implementation also involves simplifications (notably, using AR(1) models) due to the complexities of full Vector Autoregression (VAR) models in Pine Script®. █ HOW IT WORKS The indicator's methodology is based on comparing the performance of Autoregressive (AR) models: 1. Data Preprocessing: Fetches historical close prices for two user-defined symbols (X and Y). Optionally applies first-order differencing (`price - price `) to the series. Differencing is a common technique to achieve a proxy for stationarity, which is an underlying assumption for Granger Causality tests. Non-stationary series can lead to spurious correlations. 2. Autoregressive (AR) Models (Simplified to AR(1)): Due to Pine Script's current limitations for complex multivariate time series models, this indicator uses simplified AR(1) models (where the current value is predicted by its immediately preceding value). Restricted Model (for Y → Y): Predicts the target series (e.g., Y) using only its own past value (Y ). `Y = c_R + a_R * Y + residuals_R` The variance of `residuals_R` (Var_R) is calculated. Unrestricted Model (Proxy for X → Y): To test if X Granger-causes Y, the indicator examines if the past values of X (X ) can explain the residuals from the restricted model of Y. `residuals_R = c_UR' + b_UR * X + residuals_UR` The variance of these final `residuals_UR` (Var_UR) is calculated. The same process is repeated to test if Y Granger-causes X. 3. Granger Causality (GC) Score Calculation: The GC Score quantifies the improvement in prediction from adding the other series' past values. It's calculated as: `GC Score = 1 - (Var_UR / Var_R)` A score closer to 1 suggests that the "causing" series significantly reduces the unexplained variance of the "target" series (i.e., Var_UR is much smaller than Var_R), indicating stronger Granger causality. A score near 0 (or capped at 0 if Var_UR >= Var_R) suggests little to no improvement in prediction. The score is calculated over a rolling `Calculation Window`. Pine Script® Snippet (Conceptual GC Score Logic): // Conceptual representation of GC Score calculation // var_R: Variance of residuals when Y is predicted by Y // var_UR: Variance of residuals when Y's AR(1) residuals are predicted by X score = 0.0 if var_R > 1e-9 // Avoid division by zero score := 1.0 - (var_UR / var_R) score := score < 0 ? 0 : score // Ensure score is not negative 4. Determining Causal Flow: The calculated GC Scores for X → Y and Y → X are compared against a user-defined `Significance Threshold for GC Score`. If GC_X→Y > threshold AND GC_Y→X > threshold: Bidirectional flow. If GC_X→Y > threshold only: X → Y flow. If GC_Y→X > threshold only: Y → X flow. Otherwise: No significant flow. █ HOW TO USE IT Interpreting the Visuals: Background Color: Green: Indicates X → Y (Symbol 1 potentially leads Symbol 2). Orange: Indicates Y → X (Symbol 2 potentially leads Symbol 1). Blue: Indicates Bidirectional influence. Gray: No significant Granger causality detected based on the threshold. Data Window Plots: The actual GC Scores for X → Y (blue) and Y → X (red) are plotted and visible in TradingView's Data Window. A dashed gray line shows your `Significance Threshold`. On-Chart Table (Last Bar): Displays the currently detected causal direction text (e.g., "BTCUSDT → QQQ"). Potential Applications: Intermarket Analysis: Explore potential lead-lag relationships between different asset classes (e.g., commodities and equities, bonds and currencies). Pair Trading Components: Identify if one component of a potential pair tends to lead the other. Confirmation Tool: Use alongside other analyses to see if a move in one asset might foreshadow a move in another. Considerations: Symbol Choice: Select symbols that have a plausible economic or market relationship. Stationarity: Granger Causality tests ideally require stationary time series. The `Use Differencing` option is a simple proxy. True stationarity testing is complex. Non-stationary data can yield misleading results. Lag Order (p): This indicator is fixed at p=1 due to Pine Script® limitations. In rigorous analysis, selecting the optimal lag order is crucial. Calculation Window: Shorter windows are more responsive but may be noisier. Longer windows provide smoother scores but lag more. Significance Threshold: Adjust this based on your desired sensitivity for detecting causal links. There's no universally "correct" threshold; it depends on the context and noise level of the series. █ INPUTS Symbol 1 (X): The first symbol in the analysis. Symbol 2 (Y): The second symbol (considered the target when testing X → Y). Use Differencing: If true, applies first-order differencing to both series as a proxy for stationarity. Calculation Window (N): Lookback period for AR model coefficient estimation and variance calculations. Lag Order (p): Currently fixed at 1. This defines the lag used (e.g., X , Y ) in the AR models. Significance Threshold for GC Score: A value between 0.01 and 0.99. The calculated GC Score must exceed this to be considered significant. █ VISUALIZATION Background Color: Dynamically changes based on the detected Granger causal flow (Green for X → Y, Orange for Y → X, Blue for Bidirectional, Gray for None). GC Scores (Data Window): Blue Plot: GC Score for X → Y. Red Plot: GC Score for Y → X. Significance Threshold Line: A dashed gray horizontal line plotted at the level of your input threshold. On-Chart Table: Displayed on the top-right (on the last bar), showing the current causal direction text. █ ALERTS The indicator can generate alerts for: Emergence of X → Y causality. Emergence of Y → X causality. General change or cessation of a previously detected causal relationship. █ IMPORTANT DISCLAIMERS & LIMITATIONS Correlation vs. Causation: Granger causality measures predictive power, not true underlying economic causation. A strong GC Score doesn't prove one asset *causes* another to move, only that its past values improve predictions. Stationarity Assumption: While differencing is offered, it's a simplified approach. Non-stationary data can lead to spurious (false) Granger causality detection. Model Simplification (AR(1)): This script uses AR(1) models for simplicity. Real-world relationships can involve more complex dynamics and higher lag orders. The fixed lag of p=1 is a significant constraint. Sensitivity to Parameters: Results can be sensitive to the chosen symbols, calculation window, differencing option, and significance threshold. No Statistical Significance Testing (p-values): This indicator uses a direct threshold on the GC Score itself, not a formal statistical test (like an F-test producing p-values) typically found in econometric software. Use this indicator as an exploratory tool within a broader analytical framework. Do not rely on it as a standalone basis for trading decisions. █ CREDITS & LICENSE Author: mastertop ( Twitter: x.com ) Version: 1.0 (Released: 2025-05-08) This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org © mastertop, 2025
Pine Script®指標
由MASTERTOP_ASTRAY提供
Adaptive Hurst Exponent Regime FilterAdaptive Hurst Exponent Regime Filter (AHERF) █ OVERVIEW The Adaptive Hurst Exponent Regime Filter (AHERF) is designed to identify the prevailing market regime—be it Trending, Mean-Reverting, or a Random Walk/Transition phase. While the Hurst Exponent is a well-known tool for this purpose, AHERF introduces a key innovation: an adaptive threshold . Instead of relying solely on the traditional fixed 0.5 Hurst value, this indicator's threshold dynamically adjusts based on current market volatility, aiming to provide more nuanced and responsive regime classifications. This tool can assist traders in: Gauging the current character of the market. Tailoring trading strategies to the identified regime (e.g., deploying trend-following systems in Trending markets or mean-reversion tactics in Mean-Reverting conditions). Filtering out trades that may be counterproductive to the dominant market behavior. █ HOW IT WORKS The indicator operates through the following key calculations: 1. Hurst Exponent Calculation: The script computes an approximate Hurst Exponent (H). It utilizes log price changes as its input series. The `calculateHurst` function implements a variance scaling approach: It defines three sub-periods based on the main `Hurst Lookback Period`. It calculates the standard deviation of the input series over these sub-periods. The Hurst Exponent is then estimated from the slope of a log-log regression between the standard deviations and their respective sub-period lengths. A simplified calculation using the first and last sub-periods is performed: `H = (log(StdDev3) - log(StdDev1)) / (log(N3) - log(N1))`. Theoretically, a Hurst Exponent: H > 0.5 suggests persistence (trending behavior). H < 0.5 suggests anti-persistence (mean-reverting behavior). H ≈ 0.5 suggests a random walk (unpredictable movement). Pine Script® Snippet (Hurst Calculation Call): float logPriceChange = math.log(close) - math.log(close ); // ... ensure logPriceChange is not na on first bar ... float hurstValue = calculateHurst(logPriceChange, hurstLookbackInput); 2. Volatility Proxy Calculation: To enable the adaptive nature of the threshold, a volatility proxy is calculated. Users can select the `Volatility Metric` to be either: Average True Range (ATR), normalized by the closing price. Standard Deviation (StdDev) of simple price returns. This proxy quantifies the current degree of price activity or fluctuation in the market. Pine Script® Snippet (Volatility Proxy Call): float volatilityProxy = getVolatilityProxy(volatilityMetricInput, volatilityLookbackInput); 3. Adaptive Threshold Calculation: This is the core of AHERF's adaptability. Instead of a static 0.5 line as the sole determinant, the script computes a dynamic threshold. The adaptive threshold is calculated as: `0.5 + (Threshold Sensitivity * Volatility Proxy)`. This means the threshold starts at the baseline 0.5 level and then adjusts upwards or downwards based on the current `volatilityProxy` scaled by the `Threshold Sensitivity (k)` input. Pine Script® Snippet (Adaptive Threshold Calculation): float adaptiveThreshold = 0.5 + sensitivityInput * nz(volatilityProxy, 0.0); 4. Regime Identification: The prevailing market regime is determined by comparing the `hurstValue` to this `adaptiveThreshold`, incorporating a `Threshold Buffer` to reduce noise and clearly delineate zones: Trending: `hurstValue > adaptiveThreshold + bufferInput` Mean-Reverting: `hurstValue < adaptiveThreshold - bufferInput` Random/Transition: Otherwise (Hurst value is within the buffer zone around the adaptive threshold). Pine Script® Snippet (Regime Determination Logic): if not na(hurstValue) and not na(adaptiveThreshold) if hurstValue > adaptiveThreshold + bufferInput currentRegimeColor := TRENDING_COLOR regimeText := "Trending" else if hurstValue < adaptiveThreshold - bufferInput currentRegimeColor := MEAN_REVERTING_COLOR regimeText := "Mean-Reverting" // else remains Random/Transition █ HOW TO USE IT Interpreting the Visuals: Observe the plotted `Hurst Exponent (H)` line (White) relative to the `Adaptive Threshold` line (Orange). The background color provides an immediate indication of the current regime: Green for Trending, Red for Mean-Reverting, and Gray for Random/Transition. The fixed `0.5 Level` (Dashed Gray) is plotted for reference against traditional Hurst interpretation. Labels "T", "M", and "R" appear below bars to signal new entries into Trending, Mean-Reverting, or Random/Transition regimes, respectively. Inputs Customization: Hurst Exponent Calculation Hurst Lookback Period: Defines the number of bars used for the Hurst Exponent calculation. Longer periods generally yield smoother Hurst values, reflecting longer-term market memory. Shorter periods are more responsive. Adaptive Threshold Settings Volatility Metric: Choose "ATR" or "StdDev" to drive the adaptive threshold. Experiment to see which best suits the asset. Volatility Lookback: The lookback period for the selected volatility metric. Threshold Sensitivity (k): A crucial multiplier determining how strongly volatility influences the adaptive threshold. Higher values mean volatility has a greater impact, potentially widening or shifting the regime bands more significantly. Threshold Buffer: Creates a neutral zone around the adaptive threshold. This helps prevent overly frequent regime shifts due_to minor Hurst fluctuations. █ ORIGINALITY AND USEFULNESS The AHERF indicator distinguishes itself by: Implementing an adaptive threshold mechanism for Hurst Exponent analysis. This threshold dynamically responds to changes in market volatility, offering a more flexible approach than a fixed 0.5 reference, potentially leading to more contextually relevant regime detection. Providing clear, at-a-glance visualization of market regimes through background coloring and distinct plot shapes. Offering user-configurable parameters for both the Hurst calculation and the adaptive threshold components, allowing for tuning across various assets and timeframes. Traders can leverage AHERF to better align their chosen strategies with the prevailing market character, potentially enhancing trade filtering and decision-making processes. █ VISUALIZATION The indicator plots the following in a separate pane: Hurst Exponent (H): A white line representing the calculated Hurst value. Adaptive Threshold: An orange line representing the dynamic threshold. Fixed 0.5 Level: A dashed gray horizontal line for traditional Hurst reference. Background Color: Changes based on the identified regime: Green: Trending regime. Red: Mean-Reverting regime. Gray: Random/Transition regime. Regime Entry Shapes: Plotted below the price bars (forced overlay for visibility): "T" (Green Label): Signals entry into a Trending regime. "M" (Teal Label): Signals entry into a Mean-Reverting regime. "R" (Cyan Label): Signals entry into a Random/Transition regime. █ ALERTS The script provides alert conditions for changes in the market regime: Regime Shift to Trending: Triggers when the Hurst Exponent crosses above the adaptive threshold into a Trending state. Regime Shift to Mean-Reverting: Triggers when the Hurst Exponent crosses below the adaptive threshold into a Mean-Reverting state. Regime Shift to Random/Transition: Triggers when the Hurst Exponent enters the Random/Transition zone around the adaptive threshold. These can be configured directly from the TradingView alerts panel. █ NOTES & DISCLAIMERS The Hurst Exponent calculation is an approximation; various methods exist, each with its nuances. The performance and relevance of the identified regimes can differ across financial instruments and timeframes. Parameter tuning is recommended. This indicator is intended as a decision-support tool and should not be the sole basis for trading decisions. Always integrate its signals within a broader analytical framework. Past performance of any trading system or indicator, including those derived from AHERF, is not indicative of future results. █ CREDITS & LICENSE Author: mastertop ( Twitter: x.com ) Color Palette: Uses the `MaterialPalette` library by MASTERTOP_ASTRAY. This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org © mastertop, 2025
Pine Script®指標
由MASTERTOP_ASTRAY提供
Golden Khaled Recovery v2.0 – Dual Direction Dynamic //@version=5 indicator("Golden Khaled Recovery v2.0 – Dual Direction Dynamic", overlay=true) // === الإعدادات === mode = input.string("Both", title="Signal Mode", options= ) enableWatch = input.bool(true, title="Show Watch Signals (Weak Setup)") showConditionCount = input.bool(true, title="Show Conditions Count Below Candle") // === المؤشرات === macdFast = input.int(12, "MACD Fast") macdSlow = input.int(26, "MACD Slow") macdSignal = input.int(9, "MACD Signal") rsiPeriod = input.int(14, "RSI Period") volumeSpikeMultiplier = input.float(1.5, "Volume Spike Multiplier") // === حساب المؤشرات === = ta.macd(close, macdFast, macdSlow, macdSignal) rsi = ta.rsi(close, rsiPeriod) volumeSpike = volume > ta.sma(volume, 20) * volumeSpikeMultiplier // === شروط الشراء === buy1 = macdLine > signalLine buy2 = rsi < 30 buy3 = ta.crossover(macdLine, signalLine) buy4 = volumeSpike buy5 = close > ta.highest(close, 10) buyCount = (buy1 ? 1 : 0) + (buy2 ? 1 : 0) + (buy3 ? 1 : 0) + (buy4 ? 1 : 0) + (buy5 ? 1 : 0) // === شروط البيع === sell1 = macdLine < signalLine sell2 = rsi > 70 sell3 = ta.crossunder(macdLine, signalLine) sell4 = volumeSpike sell5 = close < ta.lowest(close, 10) sellCount = (sell1 ? 1 : 0) + (sell2 ? 1 : 0) + (sell3 ? 1 : 0) + (sell4 ? 1 : 0) + (sell5 ? 1 : 0) // === إشارات الشراء === plotshape((mode == "Buy" or mode == "Both") and buyCount == 5, title="BUY", location=location.abovebar, color=color.green, style=shape.labelup, text="BUY", textcolor=color.white) plotshape((mode == "Buy" or mode == "Both") and buyCount >= 3 and buyCount < 5, title="BUY+", location=location.abovebar, color=color.lime, style=shape.labelup, text="BUY+", textcolor=color.black) plotshape((mode == "Buy" or mode == "Both") and buyCount == 2 and enableWatch, title="Watch", location=location.abovebar, color=color.yellow, style=shape.triangleup, text="Watch", textcolor=color.black) // === إشارات البيع === plotshape((mode == "Sell" or mode == "Both") and sellCount == 5, title="SELL", location=location.belowbar, color=color.red, style=shape.labeldown, text="SELL", textcolor=color.white) plotshape((mode == "Sell" or mode == "Both") and sellCount >= 3 and sellCount < 5, title="SELL+", location=location.belowbar, color=color.maroon, style=shape.labeldown, text="SELL+", textcolor=color.white) plotshape((mode == "Sell" or mode == "Both") and sellCount == 2 and enableWatch, title="WatchSell", location=location.belowbar, color=color.gray, style=shape.triangledown, text="Watch", textcolor=color.black) // === عداد الشروط تحت الشمعة === if showConditionCount and buyCount >= 3 label.new(bar_index, low, str.tostring(buyCount) + "/5", yloc=yloc.belowbar, style=label.style_label_down, textcolor=color.white, size=size.tiny, color=color.black) if showConditionCount and sellCount >= 3 label.new(bar_index, high, str.tostring(sellCount) + "/5", yloc=yloc.abovebar, style=label.style_label_up, textcolor=color.white, size=size.tiny, color=color.red)
Pine Script®指標
由kalharrby提供
Golden Khaled Recovery v2.0 – Dual Direction Dynamic //@version=5 indicator("Golden Khaled Recovery v2.0 – Dual Direction Dynamic", overlay=true) // === الإعدادات === mode = input.string("Both", title="Signal Mode", options= ) enableWatch = input.bool(true, title="Show Watch Signals (Weak Setup)") showConditionCount = input.bool(true, title="Show Conditions Count Below Candle") // === المؤشرات === macdFast = input.int(12, "MACD Fast") macdSlow = input.int(26, "MACD Slow") macdSignal = input.int(9, "MACD Signal") rsiPeriod = input.int(14, "RSI Period") volumeSpikeMultiplier = input.float(1.5, "Volume Spike Multiplier") // === حساب المؤشرات === = ta.macd(close, macdFast, macdSlow, macdSignal) rsi = ta.rsi(close, rsiPeriod) volumeSpike = volume > ta.sma(volume, 20) * volumeSpikeMultiplier // === شروط الشراء === buy1 = macdLine > signalLine buy2 = rsi < 30 buy3 = ta.crossover(macdLine, signalLine) buy4 = volumeSpike buy5 = close > ta.highest(close, 10) buyCount = (buy1 ? 1 : 0) + (buy2 ? 1 : 0) + (buy3 ? 1 : 0) + (buy4 ? 1 : 0) + (buy5 ? 1 : 0) // === شروط البيع === sell1 = macdLine < signalLine sell2 = rsi > 70 sell3 = ta.crossunder(macdLine, signalLine) sell4 = volumeSpike sell5 = close < ta.lowest(close, 10) sellCount = (sell1 ? 1 : 0) + (sell2 ? 1 : 0) + (sell3 ? 1 : 0) + (sell4 ? 1 : 0) + (sell5 ? 1 : 0) // === إشارات الشراء === plotshape((mode == "Buy" or mode == "Both") and buyCount == 5, title="BUY", location=location.abovebar, color=color.green, style=shape.labelup, text="BUY", textcolor=color.white) plotshape((mode == "Buy" or mode == "Both") and buyCount >= 3 and buyCount < 5, title="BUY+", location=location.abovebar, color=color.lime, style=shape.labelup, text="BUY+", textcolor=color.black) plotshape((mode == "Buy" or mode == "Both") and buyCount == 2 and enableWatch, title="Watch", location=location.abovebar, color=color.yellow, style=shape.triangleup, text="Watch", textcolor=color.black) // === إشارات البيع === plotshape((mode == "Sell" or mode == "Both") and sellCount == 5, title="SELL", location=location.belowbar, color=color.red, style=shape.labeldown, text="SELL", textcolor=color.white) plotshape((mode == "Sell" or mode == "Both") and sellCount >= 3 and sellCount < 5, title="SELL+", location=location.belowbar, color=color.maroon, style=shape.labeldown, text="SELL+", textcolor=color.white) plotshape((mode == "Sell" or mode == "Both") and sellCount == 2 and enableWatch, title="WatchSell", location=location.belowbar, color=color.gray, style=shape.triangledown, text="Watch", textcolor=color.black) // === عداد الشروط تحت الشمعة === if showConditionCount and buyCount >= 3 label.new(bar_index, low, str.tostring(buyCount) + "/5", yloc=yloc.belowbar, style=label.style_label_down, textcolor=color.white, size=size.tiny, color=color.black) if showConditionCount and sellCount >= 3 label.new(bar_index, high, str.tostring(sellCount) + "/5", yloc=yloc.abovebar, style=label.style_label_up, textcolor=color.white, size=size.tiny, color=color.red)
Pine Script®指標
由kalharrby提供
Golden Ultra Entry v1.0 – Scalping & Swing Edition //@version=5 indicator("Golden Ultra Entry v1.0 – Scalping & Swing Edition", overlay=true, max_bars_back=1000) // === Input Settings === showWatch = input.bool(true, "Show Watch Signals") showTP = input.bool(true, "Show TP Levels") mode = input.string("Auto", options= , title="Mode") // === Indicator Calculations === rsi = ta.rsi(close, 14) cci = ta.cci(close, 20) volumeDelta = volume - ta.sma(volume, 20) netLiquidity = volumeDelta * (close - open) // === Structure Detection (Simplified for demo) === var float lastHigh = na var float lastLow = na bos = false choch = false if not na(high ) and high > high lastHigh := high if not na(low ) and low < low lastLow := low bos := close > lastHigh choch := close < lastLow // === Rejection Candle (Body < 40% of total range) === body = math.abs(close - open) fullRange = high - low rejectionCandle = body < fullRange * 0.4 // === OB Zone Placeholder === inOrderBlock = true // To be improved // === Conditions === cond1 = bos or choch cond2 = netLiquidity > 0 cond3 = rejectionCandle and inOrderBlock cond4 = mode == "Calls Only" ? rsi > 50 : mode == "Puts Only" ? rsi < 50 : true cond5 = mode == "Calls Only" ? cci > 100 : mode == "Puts Only" ? cci < -100 : true cond6 = inOrderBlock score = 0 score += cond1 ? 1 : 0 score += cond2 ? 1 : 0 score += cond3 ? 1 : 0 score += cond4 ? 1 : 0 score += cond5 ? 1 : 0 score += cond6 ? 1 : 0 // === Signal Display === buySignal = score >= 6 and bos and mode != "Puts Only" sellSignal = score >= 6 and choch and mode != "Calls Only" buyPlus = score == 4 or score == 5 sellPlus = score == 4 or score == 5 buyWatch = score == 3 sellWatch = score == 3 plotshape(buySignal, title="BUY Strong", location=location.belowbar, color=color.lime, style=shape.labelup, text="BUY") plotshape(buyPlus, title="BUY+", location=location.belowbar, color=color.green, style=shape.labelup, text="BUY+") plotshape(buyWatch and showWatch, title="BUY Watch", location=location.belowbar, color=color.yellow, style=shape.labelup, text="Watch") plotshape(sellSignal, title="SELL Strong", location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL") plotshape(sellPlus, title="SELL+", location=location.abovebar, color=color.maroon, style=shape.labeldown, text="SELL+") plotshape(sellWatch and showWatch, title="SELL Watch", location=location.abovebar, color=color.orange, style=shape.labeldown, text="Watch") // === TP/SL Placeholder === tp1 = close + (close - lastLow) * 0.5 tp2 = close + (close - lastLow) tp3 = close + (close - lastLow) * 2 sl = lastLow plot(showTP and buySignal ? tp1 : na, title="TP1", color=color.new(color.green, 50), style=plot.style_linebr) plot(showTP and buySignal ? tp2 : na, title="TP2", color=color.new(color.green, 70), style=plot.style_linebr) plot(showTP and buySignal ? tp3 : na, title="TP3", color=color.new(color.green, 90), style=plot.style_linebr) plot(showTP and buySignal ? sl : na, title="SL", color=color.new(color.red, 80), style=plot.style_linebr)
Pine Script®指標
由kalharrby提供
Z-score filter Daily/Weeklyindicator identifies potential buy and sell signals based on price deviations from a linear regression line. Here's what it does: Calculates a linear regression line with customizable length (default 21) and offset (default 30) Computes a z-score by measuring how many standard deviations the current price is from the regression line Generates signals when: A "buy" signal occurs when the z-score crosses above a lower threshold (default -4.7), indicating the price was deeply undervalued but is now recovering A "sell" signal occurs when the z-score crosses below an upper threshold (default 5.1), indicating the price was extremely overvalued but is now declining The indicator displays triangles with "BUY" or "SELL" text when signals occur, and shows the linear regression line in blue (which can be toggled off). It can operate on either daily or weekly timeframes based on user selection, with corresponding alerts that can be configured. This indicator essentially identifies potential reversal points when price has moved too far away from its statistical "fair value" as defined by the regression line, making it useful for mean-reversion trading strategies.
Pine Script®指標
由whitekidspaz提供
PORTFOLIO TABLE Full [Titans_Invest]PORTFOLIO TABLE Full This is a complete table for monitoring your assets or cryptocurrencies in your SPOT wallet without needing to access your broker’s website or app. ⯁ HOW TO USE THIS TABLE❓ Simply select the asset and enter the amount you hold. The table will display the value of each asset and the total value of your portfolio. You can monitor up to 19 assets in real time. ⯁ CONVERT VALUES You can also enable and select a currency for conversion. For example, cryptocurrencies are calculated in US dollars by default, but you can choose euros as the conversion currency. The values originally in dollars will then be displayed in euros. ⯁ TRACK THE DAILY VARIATION OF YOUR PORTFOLIO You’ll be able to monitor your portfolio’s raw daily variation in real time. 🔶 Track your Portfolio in real time: 🔶 Add your local Currency to Convert Values: 🔶 Follow your Portfolio Live: ___________________________________________________________ 📜 SCRIPT : PORTFOLIO TABLE Full 🎴 Art by  : @Titans_Invest & @DiFlip 👨‍💻 Dev by : @Titans_Invest & @DiFlip 🎑 Titans Invest — The Wizards Without Gloves 🧤 ✨ Enjoy! ___________________________________________________________ o Mission 🗺 • Inspire Traders to manifest Magic in the Market. o Vision 𐓏 • To elevate collective Energy 𐓷𐓏
Pine Script®指標
由Titans_Invest提供
REGIME SHIFTis designed to identify market regimes based on price position relative to a linear regression line. Here's what it does: Calculates a linear regression line (reg) Identifies three possible states: "Above regime": When the current close price AND previous close price are both above the regression line "Below regime": When the current close price AND previous close price are both below the regression line "Flat regime": When neither of the above conditions are true (transitioning between regimes) The indicator visualizes these states with: Green background when price is in the "Above regime" Red background when price is in the "Below regime" Yellow "FLAT" arrow markers displayed when in the "Flat regime" The regression line itself (which can be turned off via user input), colored green when above price and red when below price This indicator helps traders identify whether the market is in an uptrend regime (price consistently above regression line), downtrend regime (price consistently below regression line), or transitioning between regimes (flat). The regression line provides a statistical reference point for price action, helping to filter out noise and identify the underlying trend direction.
Pine Script®指標
由whitekidspaz提供